Reading, editing and visualizing Raster tiffs in Python

RasterReader.py

import rasterio
from numpy import copy, random, arange
import numpy as np
from matplotlib import pyplot
from matplotlib.colors import LinearSegmentedColormap

#Reading
dataset = rasterio.open('raster.tif')
#example raster is from https://daac.ornl.gov/VEGETATION/guides/Decadal_LULC_India.html
data=dataset.read(1)
#this data is a numpy 2D array with 20 classes from 0-19 with no value as 127

#Editing
#to replace the class values to make only two classe values, 0 for urban and 1 for other classes, 3 is urban in tiff numpy array
# based on [this](https://stackoverflow.com/questions/3403973/fast-replacement-of-values-in-a-numpy-array)

d = {3: 0, 2: 1, 7: 1, 10: 1, 11: 1, 1: 1, 4: 1, 5: 1, 12: 1,14:1,15:1,16:1,19:1,6:1,8:1,13:1,18:1,9:1,17:1,127:1}
dk = d.keys()
dv = d.values()

def f1(a, d):
    b = copy(a)
    for k, v in d.iteritems():
        b[a==k] = v
    return b

data1=f1(data,d)

#to get the statics of raster, the tiff each pixel is 100 meters, so each numpy array element is 100 meters, 
#to get the statsics of classes in the numpy array, gives the report in dict
unique, counts = np.unique(data1, return_counts=True)
dattif=dict(zip(unique, counts))
dattif

#visualize 
# a custom color map is requered to have simple two colour visualization based on [this](https://stackoverflow.com/questions/32524471/custom-colormap-in-python)
cmap = LinearSegmentedColormap.from_list('mycmap', ['red', 'black'])
pyplot.imshow(data1, cmap=cmap)